code: def test_override_compiling_phase():
      class MyHyperEfficientNet(efficientnet.HyperEfficientNet):
          def _compile(self, model, hp):
              learning_rate = 0.1
              optimizer_name = hp.Choice(
                  "optimizer", ["adam", "sgd"], default="adam"
              )
              if optimizer_name == "sgd":
                  optimizer = keras.optimizers.SGD(
                      momentum=0.1, learning_rate=learning_rate
                  )
              elif optimizer_name == "adam":
                  optimizer = keras.optimizers.Adam(
                      learning_rate=learning_rate
                  )
              model.compile(
                  optimizer=optimizer,
                  loss="categorical_crossentropy",
                  metrics=["accuracy"],
              )
  
      hp = hp_module.HyperParameters()
      hypermodel = MyHyperEfficientNet(
          input_shape=INPUT_SHAPE_32, classes=5
      )
      hypermodel.build(hp)
      assert "learning_rate" not in hp.values
      assert hp.values["optimizer"] == "adam"
  
file_path: keras-tuner/keras_tuner/applications/efficientnet_test.py
imports: import numpy
  import pytest
  from keras_tuner.applications import efficientnet
  from keras_tuner.backend import config
  from keras_tuner.backend import keras
  from keras_tuner.engine import hypermodel
  from keras_tuner.engine import hyperparameters
label_desc: Use image node_id 5 for calling a global function with example usage: test_override_compiling_phase() without return types